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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The GREEN ‘omics of Nutrient Feedbacks to Soil Warming

The GREEN ‘omics of Nutrient Feedbacks in Soil project advanced the DOE Biological and Environmental Research (BER) mission by developing and applying isotope-enabled ’omics tools to understand how soil microbes regulate carbon and nutrient cycling. Guided by the Growth Rate, growth Efficiency, and stoichiometry of Essential Nutrients (GREEN ’omics) framework, the project aimed to build a predictive, systems-level understanding of microbial traits that control ecosystem biogeochemistry. In a collaboration among Northern Arizona University (lead), West Virginia University, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory, we combined quantitative stable isotope probing (qSIP), Chip-SIP, NanoSIMS, and genome-resolved metagenomics across long-term experiments in Arctic, boreal, temperate, and tropical ecosystems. The project produced three key outcomes: 1) We showed that community-weighted temperature sensitivities of bacterial growth (Q10) can predict ecosystem-scale soil respiration responses across diverse soils. 2) We provided the first in situ evidence for density-dependent population dynamics in soil bacteria and demonstrated that nutrient additions intensify competition, concentrating carbon use into fewer taxa. 3) We improved and extended isotope-enabled ’omics methods by quantifying qSIP measurement error to guide experimental design and coupling SIP with genome-resolved metagenomics to reveal cross-kingdom interactions among bacteria, fungi, and viruses. Together, these results show that a small number of microbial traits and taxa exert disproportionate control over soil carbon and nutrient cycling, providing critical data and methods to improve representation of microbial processes in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Search for a Cloud Phase Feedback in the Arctic Climate System

This project was motivated by a hypothesis involving the transition in lower troposphere temperatures across the freezing point of water. Specifically, at temperatures just below to about ten degrees below freezing, Arctic clouds should be in a mixed-phase, with strong influences from secondary ice production (e.g., the Hallett-Mossop process). At temperatures just above freezing, clouds should become entirely deglaciated. We hypothesized that, with multiple years of ARM data, a statistically significant change could be detected in cloud radiative properties and surface radiative fluxes that could be directly attributed to this phase change. Furthermore, in a gradually warming climate, these phase change-related responses in surface radiation would represent a cloud phase feedback as part of Arctic amplification. We designed this research project to coincide with a new ARM Arctic cloud radar product developed by Ed Luke and collaborators at BNL (Luke et al., 2021: PNAS, doi:10.1073/pnas.2021387118) that explicitly contains SIP cloud properties retrieved from radar data. This research project has successfully concluded after analysis of a much larger North Slope of Alaska (NSA) data sample than originally anticipated, and the results are quite different than originally hypothesized.

58 GEOSCIENCES↗
DOE OSTI2026

Examining the Impacts of Microphysical-Dynamical Feedbacks on Convective Clouds in Different Aerosol Environments Using Enhanced Observational and Modeling Strategies

This project investigated how microphysical–dynamical feedbacks influence deep convective clouds across a range of aerosol conditions, storm lifecycles, and meteorological regimes, and how these sensitivities depend on the modeling framework used to represent convection and microphysics. Using the Aerosol, Cloud, Precipitation, and Climate (ACPC) Working Group model intercomparison simulations of isolated deep convection in the Houston region, we found a robust warm-phase aerosol response in most cloud-resolving models. Increased aerosol loading tended to suppress warm-rain production, increase cloud water, and reduce surface rainfall and near-surface evaporation. These impacts were typically strongest early in the convective lifecycle, with the largest aerosol-driven differences occurring during the first half of storm evolution. The ice-phase response, on the other hand, varied widely across modeling frameworks, and differed in sign, timing, and vertical structure. Ice microphysical pathways and parameterizations are therefore leading sources of uncertainty in aerosol–deep convection interactions. Theoretical analyses further suggested that aerosol-driven invigoration through cold-phase processes was much weaker than previously hypothesized for cold-based storms, and in warm-based storms could even reduce updraft strength. These results imply that any invigoration signal is more likely linked to warm-phase processes and peaks early in storm development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Closure models for the feedback of energetic particles on plasma turbulence

Energetic particles interact with the plasma surrounding them, resonating with certain types of plasma waves to stabilize them while destabilizing others, and changing the character of the background turbulence in ways that have not been fully quantified or understood. Interaction with the turbulent background plasma is key to the acceleration of many types of energetic particles including high-energy cosmic rays, solar energetic particles, and pick-up ions. The acceleration of particles is a process that would ideally be described by a kinetic model, a type of model that follows a probability distribution function (PDF) for all particles in 7-dimensional (x, y, z, v x , v y , v z , t) space. Because of the high dimensionality of a kinetic model, simulations that solve kinetic equations use the largest computational resources currently available, and are yet unable to simulate a realistic number of particles, reach the large scales necessary for astrophysical problems, and use high-precision numerical methods. Two available alternatives to kinetic plasma models have been explored for this problem, with limited success. One is a multi-fluid model produced by a cumulant discarding closure, which evolves coupled equations for the velocity, magnetic field, and internal energy for both the background plasma and the fluid of energetic particles. However, simulations that solve multi-fluid magnetohydrodynamic (MHD) equations are able to include the interaction with energetic particles only in crude ways, typically as an add-on pressure term. The second alternative is to use a hybrid method to couple a fluid description of the background plasma to a kinetic model or a Fokker–Planck model for the energetic particles. These methods are hampered by the physical modeling of the coupling. In this work, we develop a new model, which follows the PDF for all particles; this can be viewed as a step toward physical realism above a multi-fluid MHD model, while also being more computationally efficient than a kinetic model. The equations we develop model both the background plasma and the energetic particles self-consistently. Over the last decade, similar PDF methods have been developed to a high level of sophistication to model reactive flows and turbulent combustion for engineering applications. For treatment of the feedback of the energetic particles on a background plasma, a PDF closure approach should evaluate the mean characteristics, including the density, with better statistical quality than will particle-sampling procedures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

LDMS New Features for Deployment in Advanced Environments and Feedback for Operations

We describe how LDMS is being used to collect application data concurrent with system data and how the low-latency availability of this data for analysis can be used for real-time data analysis and feedback in order to support efficient, resilient, and reliable system operations. Finally, we will describe current related research areas.

Brandt, James Michael [Sandia National Laboratorie↗
DOE OSTI2025

Transverse BBU Suppression with Feedback for Energy Recovery Linacs

In this study, we present beam dynamics simulations of the Strong Hadron Cooling (SHC) Energy Recovery Linac (ERL) that incorporate a feedback (FB) system designed to mitigate Beam Breakup (BBU) instabilities. The FB effectively suppresses BBU and increases the threshold current by roughly an order of magnitude. Our analysis revealed the aliasing behavior of the dominant higher-order mode (HOM) and its suppression by the FB, as evident from the power spectral density (PSD) of the beam centroid’s horizontal motion at the exit of the final linac section. Although the FB system— even when affected by noise—successfully reduced the BBU peak, it also amplified the PSD at other frequencies. These results provide important insights into BBU suppression and threshold current enhancement in ERLs.

Setiniyaz, S. [Thomas Jefferson National Accelerat↗
DOE OSTI2026

Gauging the Impact of Cosmic-ray Feedback on the Stellar Initial Mass Function

Cosmic rays (CRs) drive ionization and influence gas dynamics in molecular clouds (MCs), potentially impacting the resulting star formation outcomes. Although previous simulations of individual star formation have included methods for CR transport (CRT), none have been large enough to resolve the stellar initial mass function (IMF). We conduct numerical simulations following the collapse of a 20,000 M ⊙ MC and the subsequent star formation including CRT, both with and without CRs accelerated by winds from the young massive stars, and compare against a non-CRT simulation. We show that after the first massive stars form, the cavity produced by feedback is more pronounced in the CRT simulations because the external CRs are able to propagate inward and compress the gas into higher-density structures. This increases the subsequent star formation in the cloud; by the end of the simulation, the star formation efficiency (SFE) in the CRT simulation including stellar wind CRs is 43% higher than the non-CRT simulation. The IMF is also top-heavy in comparison, with a slope above 1 M ⊙ that is shallower by ∼20%. These effects are also present in the simulation without wind-accelerated CRs, but they are not as pronounced; the SFE is only 16% higher than the non-CRT simulation, and the IMF high-mass slope is shallower by ∼10%. These results may explain some of the observed top-heavy IMFs, which typically occur in high-CR environments such as the Galactic center.

Fitz Axen, Margot [Oak Ridge National Laboratory (↗
DOE OSTI2024

Three Quenched, Faint Dwarf Galaxies in the Direction of NGC 300: New Probes of Reionization and Internal Feedback

We report the discovery of three faint and ultra-faint dwarf galaxies -- Sculptor A, Sculptor B and Sculptor C -- in the direction of NGC 300 (D=2.0 Mpc), a Large Magellanic Cloud-mass galaxy. Deep ground-based imaging with Gemini/GMOS resolves all three dwarf galaxies into stars, each displaying a red giant branch indicative of an old, metal-poor stellar population. No young stars or HI gas are apparent, and the lack of a GALEX UV detection suggests that all three systems are quenched. Sculptor C (D=2.04$^{+0.10}_{-0.13}$ Mpc; $M_V=-9.1\pm 0.1$ mag or $L_V=(3.7^{+0.4}_{-0.3})\times 10^5L_{\odot})$ is consistent with being a satellite of NGC 300. Sculptor A (D=1.35$^{+0.22}_{-0.08}$ Mpc; $M_V=-6.9\pm 0.3$ mag or $L_V=(5^{+1}_{-1})\times 10^4 L_{\odot})$ is likely in the foreground of NGC 300 and at the extreme edge of the Local Group, analogous to the recently discovered ultra-faint Tucana B in terms of its physical properties and environment. Sculptor B (D=2.48$^{+0.21}_{-0.24}$ Mpc; $M_V=-8.1\pm 0.3$ mag or $L_V=(1.5^{+0.5}_{-0.4})\times 10^5L_{\odot})$ is likely in the background, but future distance measurements are necessary to solidify this statement. It is also of interest due to its quiescent state and low stellar mass. Both Sculptor A and B are $\gtrsim 2-4 r_{vir}$ from NGC 300 itself. The discovery of three dwarf galaxies in isolated or low-density environments offers an opportunity to study the varying effects of ram pressure stripping, reionization and internal feedback in influencing the star formation history of the faintest stellar systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Assimilating partial observation to enhance feedback control of stochastic dynamical systems

Here, in this paper, we present a novel methodology to tackle feedback optimal control problems in scenarios where the exact state of the controlled process is unknown. It integrates data assimilation techniques and optimal control solvers to manage partial observation of the state process, a common occurrence in practical scenarios. Traditional stochastic optimal control methods assume full state observation, which is often not feasible in real-world fluid dynamics control problems. Our approach underscores the significance of utilizing observational data to inform control policy design. Specifically, we introduce a kernel learning backward stochastic differential equation (SDE) filter to enhance data assimilation efficiency and propose a sample-wise stochastic optimization method within the stochastic maximum principle framework. We demonstrate the efficacy and accuracy of our method in the control of advection-diffusion-reaction flow problem and the Dubins airplane maneuvering problem with model uncertainty.

data driven↗
DOE OSTI2026

Emerging low-cloud feedback and adjustment in global satellite observations

From mid-2003 to mid-2024, a global decrease in low-cloud amount enhanced the absorption of solar radiation by 0.22±0.07 W m −2 per decade (±1σ range), accelerating the energy imbalance trend during that period (0.44 W m −2 per decade). Through controlling factor analysis, here we show that the low-cloud trend is due to a combination of cloud feedback and adjustments to greenhouse gases and aerosols (respectively 0.09±0.02, 0.05±0.03, and 0.03±0.03 W m −2 per decade), which jointly account for 74 % of the trend. The contribution of natural climate variability is weak but uncertain (0.01±0.08 W m −2 per decade), owing to a poorly constrained trend in boundary-layer inversion strength. Importantly, the observed low-cloud radiative trend lies well within the range of values simulated by contemporary global climate models under conditions close to present day. Any systematic model error in the representation of present-day global energy imbalance trends is thus likely to originate in processes unrelated to low clouds.

Geosciences↗
DOE OSTI2024

Direct Fabrication of Atomically Defined Pores in MXenes Using Feedback-Driven STEM

Controlled fabrication of nanopores in 2D materials offer the means to create robust membranes needed for ion transport and nanofiltration. Techniques for creating nanopores have relied upon either plasma etching or direct irradiation; however, aberration-corrected scanning transmission electron microscopy (STEM) offers the advantage of combining a sub-Å sized electron beam for atomic manipulation along with atomic resolution imaging. Here, for this work, a method for automated nanopore fabrication is utilized with real-time atomic visualization to enhance the mechanistic understanding of beam-induced transformations. Additionally, an electron beam simulation technique, Electron-Beam Simulator (E-BeamSim) is developed to observe the atomic movements and interactions resulting from electron beam irradiation. Using the MXene Ti 3 C 2 T x , the influence of temperature on nanopore fabrication is explored by tracking atomic transformations and find that at room temperature the electron beam irradiation induces random displacement and results in titanium pileups at the nanopore edge, which is confirmed by E-BeamSim. At elevated temperatures, after removal of the surface functional groups and with the increased mobility of atoms results in atomic transformations that lead to the selective removal of atoms layer by layer. This work can lead to the development of defect engineering techniques within functionalized MXene layers and other 2D materials.

36 MATERIALS SCIENCE↗